Method for measuring the mudguard edge of a vehicle on a test bench

ABSTRACT

In a method for measuring the wing edge of a vehicle on a test bed, the test bed has a coordinate system in which the Z-axis is the vertical axis, the X-axis is an axis on the test bed extending in the horizontal plane in the longitudinal direction of a vehicle located on the test bed for testing, and the Y-axis is an axis of the test bed extending perpendicular to the X-axis in the horizontal plane. In determining the position and orientation of the wing edge, a light pattern projected onto a vehicle by an illumination unit is moved and recorded by two imaging units. A subset for evaluation is formed from the 3D point clouds determined stereophotogrammetrically from the recordings.

The present invention relates to a method for measuring the wing edge ofa vehicle on a test bed according to claim 1.

For better visualisation of the invention, a coordinate system of thetest bed is first defined as follows. The test bed has a coordinatesystem

-   -   in which the Z-axis is the vertical axis,    -   in which the X-axis is an axis on the test bed extending in the        horizontal plane in the longitudinal direction of a vehicle        located on the test bed for testing, and    -   in which the Y-axis is an axis that extends perpendicular to the        X-axis and perpendicular to the Z-axis.

Measurement of the wing edge takes place, for example, in theapplication areas of development, production, in the after-sales fieldor in technical monitoring as regular checking of vehicles in operationfor their road safety. By measuring the wing edge, the position andorientation of the wing edge can be determined. The position and theorientation of the wing edge can be determined absolutely in thecoordinate system of the test bed or also in relation to othercomponents of the vehicle. These other components can be, for example,wheels, wheel rims and/or brake discs.

The position and orientation of the wing edge is used to determine whatis termed the “ride height” of the vehicle. This is the springdeflection of the vehicle body. The ride height is the distance of thewing edge (or of a characteristic point on the wing edge) from the wheelcentre. The Z-coordinates of the data of the position and orientation ofthe wing edge determine the ride height of the vehicle.

Apart from determining the ride height, the ascertained data of theposition and orientation of the wing edge can also be used to determinethe width of the vehicle.

To this end, the Y-coordinates of the position and orientation of thewing edge of opposing wings on the two sides of the vehicle can be used.

Devices for the photogrammetric measurement of objects are known in theform that these consist of an exposure unit and several imaging units.Light is radiated by the exposure unit. This light is scattered by theobject to be measured. The scattered light is recorded by the imagingunits. The recordings of the imaging units are evaluated. Thisevaluation gives rise to a point cloud as a three-dimensionalarrangement of the points as a data set. Here the points of the pointcloud correspond to points on the surface of the object that scattersthe light. The calculation of the point cloud is carried out using twoor more imaging units as photogrammetry.

The imaging units are cameras. The calculation and evaluation can takeplace in an evaluation device, which can be arranged downstream of theimaging units as a separate component. In this case, signals of theimaging units are supplied to the evaluation device as input signals. Itis also possible to integrate the evaluation device as a component withthe imaging units. In the evaluation device, software is implementedwhich executes the functions of calculation and evaluation.

In photogrammetry, a two-dimensionally coded texture is placed onto thesurface of the three-dimensional object to be measured via the exposureunit. “Texture” in the present context means that a defined lightpattern is involved. This texture serves as an aid when evaluating theimages recorded by the imaging units. The imaging units view the objectfrom different directions. These imaging units therefore “see” the samelight pattern on the surface from different directions. Due to thetwo-dimensionally coded exposure texture, it is then possible in theevaluation to associate the respectively corresponding points of theimaging units with one another. The position of the points is calculatedvia the image information of the imaging units in space in relation tothe coordinate system of the device for photogrammetric measurement. Theposition and orientation of the coordinate system of the device forphotogrammetric measurement is calibrated in relation to the coordinatesystem of the vehicle test bed. These points thereby give rise to athree-dimensional point cloud of the object in the coordinate system ofthe device for photogrammetric measurement. The three-dimensional pointcloud of the object in the coordinate system of the vehicle test bedalso results from this.

To achieve a high measuring accuracy when detecting the position andorientation of the wing edge, it is necessary to have a high pointdensity in the point cloud. With a high point density, the number ofpoints included in the calculation when evaluating the position andorientation of the wing edge increases. In the case of a suitably highpoint density, this requires a not inconsiderable computing time. In theproduction of vehicles in particular, calculation with a high pointdensity requires so much time with regard to evaluation that this has anegative impact on cycle times.

A device for contactless determination of the position and orientationof the wing edge of a vehicle is known from EP 0 757 229 B1. The devicecomprises first means for determining the position of a defined point ofthe body of the vehicle in the z-direction, second means for determiningthe position of the wheel centre point in the z-direction, and anevaluation unit for calculating the ride height of the vehicle from thepositions determined using the first and second means, which unit isconnected to the first and the second means.

A method is to be proposed with the present invention with which theposition and orientation of the wing edge can be determined simply.

This object is achieved according to the present invention according toclaim 1 by a method for measuring the wing edge of a vehicle on a testbed. The test bed has a coordinate system in which the Z-axis is thevertical axis, the X-axis is an axis on the test bed extending in thehorizontal plane in the longitudinal direction of a vehicle located onthe test bed for testing and the Y-axis is an axis extendingperpendicular to the X-axis and perpendicular to the Z-axis. The methodcomprises the following steps:

-   -   projection of a uniform light pattern onto a vehicle using at        least one illumination unit, wherein the light pattern can be        divided into sub-regions of equal size in such a way that the        sub-regions of the light pattern are individualised.    -   Recording, by two imaging units, the light pattern projected        onto the vehicle, wherein the two imaging units each record the        light pattern momentarily projected onto the vehicle.    -   movement of the light pattern projected onto the vehicle by        stimulating vibration of the illumination unit or at any rate at        least of one component of the illumination unit.    -   stereophotogrammetric determination of a 3D point cloud from the        recordings by the two imaging units of the light pattern        projected onto the vehicle during vibration of the illumination        unit or of the at any rate at least one component of the        illumination unit,    -   identification of a subset of points from the 3D point cloud,        wherein the subset is formed by the intersection        -   of the points of the point cloud        -   with a plurality of volumes,            -   wherein each volume is delimited by two planes, which                extend both in the direction of the Y-axis and in the                direction of the Z-axis,            -   wherein these two planes have a spacing Δx from each                other in the direction of the X-axis,            -   wherein a plurality of these volumes is located at                adjacent positions x_(n) on the X-axis,    -   determination of the position and orientation of the wing edge        as a result data set on the basis of the subset of points of the        3D point cloud.

These features signify that the light pattern as such is constant. Addedto the points in the point cloud that result from a statically emittedprojection of the light pattern onto an object, according to the presentinvention, are other points in the point cloud resulting from recordingsin which the same (uniform) light pattern is projected onto the object,wherein, however, either the illumination unit as a whole or at any rateat least one component of the illumination unit is stimulated tovibrate. This vibration leads to a movement of the projected lightpattern. The points in the point cloud are thus “supplemented” in thatthe points recorded at the moment in which the light pattern is suitablydisplaced by the vibration are “integrated” into the point cloud.

The illumination unit can be stimulated to vibrate as a whole. Theillumination unit can be constructed, for example, such that an imagethat is affixed to the illumination unit as a transparency, for example,is illuminated by a light source. In this case it is sufficient tostimulate the transparency to vibrate. This stimulation of only thetransparency is advantageous to the extent that the transparency has asmaller mass compared with the illumination unit as a whole and thusalso has a lower inertia. Vibration of the at any rate at least onecomponent of the illumination unit therefore takes place in such a waythat the light pattern projected onto the object is moved in itsposition on the object.

By moving the light pattern projected onto the vehicle, the density ofthe calculated 3D point cloud can thus advantageously be increased. Herean increase in the density of the points of the point cloud signifies areduction in the mean spacing of the points of the point cloud. Themovement is caused here by vibration of the illumination unit or at anyrate at least of one component of the illumination unit. For example,the movement of the light pattern can be achieved by vibration of aphoto plate illuminated by a lamp. The vibration can be caused, forexample, by an electric vibration motor, particularly preferably by apiezoelement.

A uniform light pattern is projected by the at least one illuminationunit onto the surface of the vehicle. Here the wing edge to be measuredis located in the region of the vehicle onto which the light pattern isprojected.

The light pattern can be divided into sub-regions of equal size in sucha way that the sub-regions of the light pattern are individualised. Thismeans that the individual sub-regions are each unique within the lightpattern. These sub-regions can particularly advantageously be determinedunambiguously within the light pattern. The light pattern can also becomposed of several light patterns with sub-regions respectivelyindividualised in the light pattern. For example, two identical lightpatterns with individualised sub-regions can be assembled into anoverall light pattern. The uniqueness of the sub-regions in the overalllight pattern results in this case from the association with one of thetwo light patterns.

One example of such a light pattern is an overall arrangement ofilluminated and non-illuminated points. The overall arrangement can bedivided such that the sub-arrangements of point patterns for the singlepoints of the overall arrangement are individualised for the singlepoints taking into account other points adjacent to each single point.This overall arrangement of illuminated and non-illuminated points cantake place as a simultaneous and monochromatic projection of thearrangement of illuminated and non-illuminated points onto the wing edgeto be measured.

Another example of a light pattern in the context of the presentinvention is a texture composed of individual surface elements, theforms of which are identical. These surface elements can be square inthis case, for example. The surface elements can directly adjoin oneanother in that the lateral edge of one square forms a lateral edge ofan adjacent surface element at the same time. The uniqueness of thesurface elements can be achieved by an absent periodicity of the markingin that the state of the individual surface elements is not periodic inthe sense of “illuminated” or “non-illuminated”. A texture is thuscreated, for example, the optical impression of which is comparable withthe optical impression of a QR code, at least when this is only viewedfleetingly. If this texture is divided into small sub-regions, forexample a square with its 8 adjacent squares, a total of 2{circumflexover ( )}9 combination options (i.e.: 512 combination options) ofilluminated and non-illuminated squares results for these 9 squares.2{circumflex over ( )}9 unique sub-regions can thus be created, whichcan be clearly assigned. If the sub-region is taken further and includesthe next squares but one, for example, this number increases by thefactor of two with each additional square.

The projected light pattern serves as a marking on the surface of thevehicle. This marking is recorded by the two imaging units. A mutualassociation of the points on the surface of the vehicle by way of themarking is thus possible in the evaluation. This is because the singlesubsets are individualised.

The illumination can advantageously be realised with a uniform lightpattern. This reduces the complexity of the illumination unit, as nodynamic light patterns or sequences of light patterns have to beproduced. In particular, no identification phase is necessary, in whichportions of the light pattern change and/or are faded in and out. Thisis sometimes necessary in the prior art to be able to carry out therebyan association of these portions with one another. It is advantageous inthis case that the capture of all points of the point cloud takes placesimultaneously. The absence of an identification phase increases themeasuring rate. “Simultaneously” means in this context that theconsecutive measurements during vibration of the illumination unit or ofthe at any rate at least one component of the illumination unit in thiscontext should be understood as a unified measurement. The proceduredescribed here of vibrating the illumination unit or the at any rate atleast one component of the illumination unit serves in the presentmethod to increase the point density. The vibration is therefore notused to be able to associate points on the surface of the vehicle atall. The vibration serves to produce additional points on the surface,so that as a whole a higher point density results.

It is advantageous in this case to select a contrast-rich light patternto improve the recognition of the light pattern projected onto thesurface of the vehicle by the imaging units. Binary patterns inparticular, in which surfaces of maximal intensity (i.e. illuminatedsurfaces) alternate with surfaces of minimal intensity (i.e.non-illuminated surfaces), offer a high contrast and are thusparticularly well suited.

The light emitted by the illumination unit can be monochromatic here.This advantageously means that the radiated light as well as thescattered light has sufficient contrast compared with the scatteredlight of the environment for the method according to the presentinvention, even without special measures of dimming and with a limitedintensity of the radiated light.

If the illumination unit has an LED as a light source, it provesadvantageous that only a short warm-up time is required for initialoperation. The device is then usually ready for use within a few minutesand requires no protracted heating of assemblies. This is particularlyadvantageous following initial operation of the device, as operationaldelays and prolongations of the cycle times in vehicle productionassociated with this can be avoided.

Stereophotogrammetric determination of the 3D point cloud takes placefrom the recordings by the two imaging units of the light patternprojected onto the vehicle during vibration of the illumination unit.Here a 3D point cloud can be determined stereophotogrammetrically fromthe image pairs of the two imaging units respectively in each movementstate as a momentary recording. The individual 3D point clouds obtainedcan be combined to give a common 3D point cloud with a higher density ofpoints. Alternatively, the image pairs of the two imaging units in aplurality of movement states can be combined by a stereo matchingalgorithm and from this a point cloud with a higher density of pointscan be obtained compared with the individual point clouds determinedstereophotogrammetrically solely from one image pair.

The subset of points from the 3D point cloud is determined by theintersection of the points of the point cloud with a plurality ofvolumes. The result is a 3D point cloud with points inside the volumes.The number of points in the subset can be increased by increasing thespacing of the two planes of the volumes in the direction of the X-axisΔx and by a larger number of volumes.

The spacing of the two planes Δx is preferably greater than the meanspacing of the points of the point cloud, but smaller than double thespacing of the points of the point cloud. Advantageously at least onerow of points is thereby located in the Z-direction for each volume inthe subset. The points in a volume thereby form a curved, substantiallyvertical line following the surface of the vehicle. The number ofvolumes can be up to 120 in this case.

The number of points for the evaluation is particularly advantageouslyreduced by the subset of the point cloud. The reduced number of pointsin the subset permits a particularly fast and efficient determination ofthe position and orientation of the wing edge. At the same time, theincreased density of the point cloud in the subset permits increasedmeasuring accuracy. As stated, the density of the point cloud isparticularly advantageously increased also by vibration of theillumination unit or of the at any rate at least one component of theillumination unit.

Particularly advantageously the wing edge can be determined especiallysimply by the points on the curved, substantially vertical line. Thewing edge can thus be determined, for example, by a change in theY-coordinates from one point on one of the lines to the next point. Thisincreases the measuring rate of measuring the position and orientationof the wing edge, because in this respect it is a very efficientprocedure that can be executed very quickly to determine the position ofthe wing edges in the points in the respective volume.

In another implementation of the inventive method according to claim 2,the data used for the evaluation is selected as follows beforedetermining the position and orientation of the wing edge.

-   -   A first reduction subset of points of the point clouds is        produced from the subset.    -   Only points of the point clouds from only a portion of the        volumes (in the sense of claim 1) are taken into account.    -   In a first evaluation step, the position and orientation data of        the wing edge is determined as a first data set based on the        points of the first reduction subset.    -   From the wing edge position and orientation data in the first        data set, the position and orientation data of the wing edge in        a second data set is determined,        -   in that supplementary to the position and orientation data            of the wing edge in the first data set, position and            orientation data of the wing edge is determined, by            extrapolation of the position and orientation data of the            wing edge of the first data set, also for the volumes that            were not taken into account in the production of the first            reduction subset and        -   in that the second data set is formed from the union of the            position and orientation data of the wing edge of the first            data set with the supplementary position and orientation            data of the wing edge.    -   A second reduction subset is produced from the subset in that        the intersection is formed from        -   the points of the point cloud of the subset        -   with a defined environment around the points of the second            data set.    -   The determination of the position and orientation of the wing        edge in the result data set takes place based on the data of the        second reduction subset.

Terminologically, identical terms to claim 4 are used in connection withclaim 2. The two claims each relate to claim 1, wherein claim 4 does notrelate to claim 2. In this respect, although the first reduction subset,the first data set and the second reduction subset and the second dataset in claim 2 are identical terminologically to claim 4, they have adifferent meaning in connection with claim 2, which results in therespective context from the features of claim 2 or from the features ofclaim 4.

The evaluation of the first data set (in claim 2) is advantageouslyaccelerated based on the smaller number of points in the first reductionsubset (in claim 2) compared with the subset.

The data of the first data set (in claim 2) can be supplementedparticularly advantageously also for the volumes not taken into accountwhen determining the position and orientation of the wing edge byextrapolating the data of the first data set (in claim 2). Suchextrapolation of the data is faster here than determination of theposition and orientation of the wing edge based on the volumes not takeninto account. In this respect a second data set is formed from the unionof the points of the first data set with the points additionallyobtained by this extrapolation.

To determine the position and orientation of the wing edge moreaccurately, a second reduction subset (in claim 2) is produced from thesubset here. In this case the intersection is formed from

-   -   the points of the subset    -   with a defined environment around the points of the second data        set (in claim 2). This environment can be configured, for        example, as a cuboid. It is also possible to define this        environment as a torus, which has the line of the wing edge        determined in the second data set as centre line. The        environment advantageously comprises all points with a defined        spacing from the points of the second data set. This spacing is        particularly advantageously dependent on the mean spacing of the        points of the first reduction subset. The defined environment        can also be determined so that it involves here all points of        which the Z-coordinates deviate in amount by no more than a        predetermined limit value from the Z-coordinates of the points        of the first data set. The Y-coordinates are thus not considered        in the “point selection”. The curve of these Y-coordinates is        considered in the subsequent evaluation in order to deduce the        position and orientation of the wing edge from a sudden change        in the Y-coordinates of points which are adjacent in the        Z-direction.

The points of the second reduction subset are used to determine theposition and orientation of the wing edge. The second reduction subsetparticularly advantageously has the same density of points of the pointcloud (point spacing) as the subset. The measuring accuracy is retainedthereby during evaluation of the position and orientation of the wingedge. By the reduction to the points around the points of the seconddata set (in the sense of claim 2), the set of points to be evaluated isreduced in comparison with the subset. The determination of the positionand orientation of the wing edge can thereby take place particularlyfast. Nevertheless, the high measuring accuracy is retained in the laststep of the evaluation in that the data in the region of interest isselected specifically for this evaluation. Higher measuring rates areadvantageously facilitated thereby.

It is expedient here as a development of claim 2 according to claim 3,when generating the first reduction subset, to incorporate only aportion of the points of the subset in the volumes taken into accountwhen producing the subset to the first reduction subset. In this casethe point spacing between the points incorporated into the firstreduction subset is greater than the point spacing in the subset.

The number of points in the first reduction subset is advantageouslyreduced further thereby, due to which an even faster evaluation of thedata of the first data set (in the sense of claim 2) is possible.

It is pertinent to the invention that according to claim 4, the dataused for evaluation is selected before determining the position andorientation of the wing edge,

-   -   in that a first reduction subset of points of the point clouds        is produced from the subset,        -   in that only a portion of the points of the subset is            incorporated into the first reduction subset,            -   wherein the point spacing between the points                incorporated into the first reduction subset is greater                than the point spacing in the subset,    -   wherein in a first evaluation step the position and orientation        data of the wing edge is determined as a first data set based on        the points of the first reduction subset,    -   wherein a second reduction subset is produced from the subset,        -   in that the intersection is formed            -   from the points of the point cloud of the subset            -   with a defined environment around the points of the                first data set,    -   wherein the determination of the position and orientation of the        wing edge takes place in the result data set based on the data        of the second reduction subset.

Terminologically, identical terms to claim 2 are used in connection withclaim 4. The two claims each relate to claim 1, wherein claim 4 does notrelate to claim 2. In this respect, although the first reduction subset,the first data set and the second reduction subset and the second dataset in claim 4 are identical terminologically to claim 2, they have adifferent meaning in connection with claim 4, which arises below in theconsideration of claim 4 in context from the features of claim 4.

Compared with the method according to claim 1, this procedure accordingto claim 4 proves advantageous. In the procedure according to claim 1, ahigh point density exists in the subset in the individual volumes overthe entire range of coordinates in the direction of the Z-axis. Thismeans that a larger number of data that are comparatively remote fromthe wing edge in the direction of the Z-axis is still contained in thesubset. In this respect some computing operations are still performedthat do not lead to any meaningful result with regard to locating thewing edge.

Using the first reduction subset in the sense of claim 4, the positionand orientation of the wing edge can be determined initially with alower point density (higher point spacing between the points) with aless precise evaluation. Here the point spacing between the pointsincorporated into the first reduction subset is greater than the pointspacing in the subset. This can be achieved, for example, by removingindividual points from the subset. For example, every second point canbe removed from the subset. It is also possible to increase the pointspacing still further. Due to the greater point spacing and the lowerdensity of the points associated with this in the first reductionsubset, a first determination of the position and orientation of thewing edge in a first data set can take place particularly quickly.

The approximate position and orientation of the wing edge are yieldedinitially by the first data set. Points of a first data set can becalculated thereby that correspond to the position and orientation ofthe wing edge. This calculation takes place on the basis of the firstreduction subset in the coordinate system of the test bed. For a moreprecise determination of the position and orientation of the wing edge,a second reduction subset is produced here from the subset. This secondreduction subset is formed by the intersection, which results from:

-   -   the points of the subset    -   with a defined environment around the points of the first data        set.

This environment can be configured, for example, as a cuboid. It is alsopossible to define this environment as a torus, which has the line ofthe wing edge determined in the first data set as centre line. Theenvironment advantageously comprises all points with a defined spacingfrom the points of the first data set. This spacing is particularlyadvantageously dependent on the mean spacing of the points of the firstreduction subset. The defined environment can also be determined so thatit involves all points of which the Z-coordinates deviate in amount bynot more than a predetermined limit value from the Z-coordinates of thepoints of the first data set. The Y-coordinates are thus not consideredin the “point selection”. The curve of these Y-coordinates is consideredin the subsequent evaluation in order to deduce the position andorientation of the wing edge from a sudden change in the Y-coordinatesof points which are adjacent in the Z-direction.

The points of the second reduction subset are used to determine theposition and orientation of the wing edge. The second reduction subsetadvantageously has the same density of points (point spacing) as thesubset. The measuring accuracy of the high resolution of the points inthe point cloud is thereby retained when determining the position andorientation of the wing edge. By reducing the points in the secondreduction subset to only the points that lie in a environment around theposition and orientation of the wing edge determined previously (with areduced measurement resolution), the set of points to be evaluated isreduced compared with the subset. This reduction takes place, however,specific to the region of interest for more accurate evaluation.Determination of the position and orientation of the wing edge therebytakes place as a whole particularly fast, but nevertheless with a highlevel of accuracy.

Higher measuring rates are advantageously enabled thereby. This provesparticularly advantageous when using the method in the production ofvehicles. This is crucially reliant on short cycle times with a highresolution and accuracy at the same time.

Exemplary embodiments of the invention are described in greater detailon the basis of drawings.

These show:

FIG. 1 a view in perspective of a wing of a vehicle, and a device forthe photogrammetric measurement of objects,

FIG. 2 a side view of a wing of a vehicle, and a device for thephotogrammetric measurement of objects,

FIG. 3 another side view of a wing of a vehicle, and a device for thephotogrammetric measurement of objects,

FIG. 4 another side view of a wing of a vehicle, and a device for thephotogrammetric measurement of objects.

FIGS. 1, 2, 3 and 4 show two imaging units 2 a and 2 b and anillumination unit 3 of a device for the photogrammetric measurement ofobjects 1. A light pattern 4 is projected onto a wing 12 of a vehicle 8via the illumination unit 3. This light pattern 4 is recorded by the twoimaging units 2 a and 2 b. The light pattern 4 projected onto thevehicle 8 is moved by stimulating vibration of the illumination unit 3or at any rate at least of one component of the illumination unit 3. Inan evaluation unit, the stereophotogrammetric determination takes placeof a 3D point cloud from the recordings by the two imaging units 2 a and2 b of the light pattern 4 projected onto the vehicle during vibrationof the illumination unit 3. This point cloud corresponds to the positionof points on the surface of the object to be measured.

The vehicle 8 has a wheel 6 mounted on the vehicle 8. The wing 12 ispart of the bodywork of the vehicle 8. The wing 12 ends in the directionof the wheel 6 at its lower end in the wing edge 7.

The vehicle 8 is located on a test bed, wherein the test bed has acoordinate system in which the Z-axis is the vertical axis, the X-axisis an axis on the test bed extending in the horizontal plane in thelongitudinal direction of the vehicle 8 located on the test bed fortesting and the Y-axis is an axis on the test bed extendingperpendicular to the X-axis in the horizontal plane. In the depiction inFIG. 2 , the Z-axis and the X-axis are shown. The Y-axis extends intothe drawing plane.

As also depicted in FIG. 2 , a subset of points is identified from thepoints of the 3D point cloud 9 in a first step. Here the subset isformed by the intersection of the points of the point cloud 9 with aplurality of volumes 10. Each volume 10 is delimited by two planes,which extend both in the direction of the Y-axis and in the direction ofthe Z-axis. These two planes have a spacing Δx from one another in thedirection of the X-axis. These volumes 10 are located at adjacentpositions x_(n) on the X-axis. Here the points of the point cloud 9inside the volumes 10 are depicted by crosses and the points of thepoint cloud 9 outside the volumes 10 are depicted by circles.

The spacing of the two planes Δx is greater than the mean spacing of thepoints of the point cloud 9, but preferably smaller than double thespacing of the points of the point cloud 9. At least one point pervolume 10 and Z-coordinate is thereby advantageously located in thesubset. The points in one volume 10 thereby form a curved andsubstantially vertical line following the surface of the vehicle. Thepoints of the curved line are located here substantially in a planeextending in the Y- and Z-direction. The determination of the positionand orientation of the wing edge 7 takes place as a result data setbased on the subset of points of the 3D point cloud 9.

FIG. 2 visualises the formation of the subset according to claim 1 inthis respect.

As depicted in FIG. 3 , a first reduction subset is produced in a secondstep from the points of the point clouds of the subset. In this caseonly a portion of the points of the subset is incorporated into thefirst reduction subset. The point spacing between the pointsincorporated into the first reduction subset is greater than the pointspacing in the subset.

The points within the subset that are received into the first reductionsubset are depicted by crosses. The points within the subset that arenot received into the first reduction subset are depicted by circles. Inthe depiction in FIG. 3 , every second point is removed from the subsetin the incorporation into the first reduction subset. Due to the greaterpoint spacing and the lower density of points associated with this inthe first reduction subset, a first, rough determination of the positionand orientation of the wing edge 7 in a first data set can take placeparticularly fast.

In this respect the depiction in FIG. 3 is a visualisation in thedetermination of the first reduction subset in the sense of claim 2. Afirst data set (in the sense of claim 2) was therefore determined, whichcorresponds to the data of the position and orientation of the wing edge7 based on the data of the first reduction subset.

As depicted in FIG. 4 , a second reduction subset is produced in afollowing step to the depiction of FIG. 3 . This takes place in that theintersection of the points of the point cloud 9 of the subset is formedwith a defined environment around the points of the first data set. Thepoints within the subset that are received into the second reductionsubset are depicted by crosses. The points within the subset that arenot received into the second reduction subset are depicted by circles.The determination of the position and orientation of the wing edge 7takes place in the result data set based on the data of the secondreduction subset.

1. A method for measuring the wing edge (7) of a vehicle (8) on a test bed,

wherein the test bed has a coordinate system, wherein in the coordinate system, the Z-axis is the vertical axis on the test bed and the X-axis is an axis on the test bed extending in the horizontal plane in the longitudinal direction of a vehicle (8) located on the test bed for testing, and the Y-axis is an axis extending perpendicular to the X-axis and perpendicular to the Z-axis,

wherein the method comprises the following steps:

projection of projecting a uniform light pattern (4) onto a vehicle (8) using at least one illumination unit (3), wherein the light pattern (4) can be divided into sub-regions of equal size such that the sub-regions of the light pattern (4) are individualised,

recording et the light pattern (4) projected onto the vehicle (8) by two imaging units (2 a, 2 b), wherein the two imaging units (2 a, 2 b) each record the light pattern (4) projected momentarily onto the vehicle (8),

moving the light pattern (4) projected onto the vehicle (8) by stimulating vibration of the illumination unit (3) or at any rate at least of one component of the illumination unit (3),

stereophotogrammetric determination of stereophotogrammetrically determining a 3D point cloud from the recordings by the two imaging units (2 a, 2 b) of the light pattern (4) projected onto the vehicle (8) during vibration of the illumination unit (3) or of the at any rate at least one component of the illumination unit (3),

identifying a subset of points from the 3D point cloud (9), wherein the subset is formed by the intersection of points of the point cloud (9) with a plurality of volumes (10), wherein each volume (10) is delimited by two planes, which extend both in the direction of the Y-axis and in the direction of the Z-axis, wherein these two planes have a spacing Δx from one another in the direction of the X-axis, wherein a plurality of these volumes (10) is located at adjacent positions x_(n) on the X-axis,

determination of determining the position and orientation of the wing edge (7) as a result data set based on the subset of the points of the 3D point cloud.
 2. The method according to claim 1, wherein before determining the position and orientation of the wing edge (7), the data used for the evaluation is selected

wherein a first reduction subset of points of the point clouds (9) is produced from the subset, wherein only points of the point clouds from only a portion of the volumes (10) are taken into account,

wherein in a first evaluation step, the position and orientation data of the wing edge (7) is determined as a first data set based on the points of the first reduction subset,

wherein from the position and orientation data of the wing edge (7) in the first data set, the position and orientation data of the wing edge (7) is determined in a second data set, wherein supplementary to the position and orientation data of the wing edge (7) in the first data set, position and orientation data of the wing edge is determined, by extrapolation of the position and orientation data of the wing edge (7) of the first data set, also for the volumes (10) that were not taken into account when producing the first reduction subset and wherein the second data set is formed from the union of the position and orientation data of the wing edge (7) of the first data set with the supplementary position and orientation data of the wing edge (7),

wherein a second reduction subset is produced from the subset, in that wherein the intersection is formed from the points of the point cloud of the subset with a defined environment around the points of the second data set,

wherein the determination of the position and orientation of the wing edge (7) in the result data set takes place based on the data of the second reduction subset.
 3. The method according to claim 2, wherein when producing the first reduction subset, only a portion of the points of the subset in the volumes (10) taken into account in production of the subset is incorporated into the first reduction subset,

wherein the point spacing between the points incorporated into the first reduction subset is greater than the point spacing in the subset.
 4. The method according to claim 1, wherein before determining the position and orientation of the wing edge (7), the data used for the evaluation is selected

wherein a first reduction subset of points of the point cloud (9) is produced from the subset, wherein only a portion of the points of the subset is incorporated into the first reduction subset, wherein the point spacing between the points incorporated into the first reduction subset is greater than the point spacing in the subset,

wherein in a first evaluation step, the position and orientation data of the wing edge (7) is determined as a first data set based on the points of the first reduction subset,

wherein a second reduction subset is produced from the subset, in that wherein the intersection is formed from the points of the point cloud in the subset with a defined environment around the points of the first data set,

wherein the determination of the position and orientation of the wing edge (7) in the result data set takes place based on the data of the second reduction subset. 